Ultra-broad sensing range, high sensitivity textile pressure sensors with heterogeneous fibre architecture and molecular interconnection strategy

Heterogeneous woven fibre architecture and interfaical modification strategy enabled high performance Silk/APTES/MXene textile pressure sensors for artificial intelligence enhanced sign language and lip motion recognition. [Display omitted] •A high sensitivity with ultra-broad sensing pressure sensor is proposed for sign language and lip motion recognition.•The designed heterogeneous fiber architecture could greatly enable rich and multi-level contact pattern and could compensate for the effect of structural stiffening, which could greatly enhance both the sensitivity and linearity.•The proposed chemical interfacial modification process could enhance the interface bonding interaction between the matrix (Silk) and functional materials (MXene), which could dramatically improve the mechanical stability of the pressure sensor.•The demonstration of a proposed sensor array that could apply to remote control an entire intelligent human–machine dialogue system through sign/lip-interact commands. Textile-based pressure sensors have garnered extensive attentions owing to their potentials in health monitoring, human–machine interactions, wearable human–machine interfaces (HMIs) and soft robotics. High sensitivity over a broad sensing range are highly desired yet challenging for textile pressure sensors due to the incompressibility of matrix materials and the stiffening of microstructures. Herein, we developed a high performance pressure sensor based on the silk/3-Aminopropyltriethoxy-silane/titanium carbide (Silk/APTES/MXene) film. The silk is designed with heterogeneous fiber architecture, which enables rich and multi-level contact pattern and could compensate for the effect of structural stiffening. Furthermore, APTES molecules are used to enhance the interface bonding between MXene and silk, promoting the mechanical stability of the sensor. Benefiting from these advantages, the Silk/APTES/MXene sensor device is achieved with high sensitivity of 17.1 KPa−1 over an ultra-broad sensing range up to 3.3 MPa (R2 = 0.997), ultra-low detection limit (0.25 Pa), and low fatigue toughness after 5000 cycles loading and unloading. With these merits, we have demonstrated its capability for a series of human motion detection (such as foot movement detection, arm/wrist/finger bending, etc) and an overall accuracy of 95 % is obtained with the help of CNN-based convolution neural architecture. More significantly, we have built an entire intelligent human–machine dialogue system and